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dc.contributor.authorunicampSantanchè, Andrépt_BR
dc.titleProvenance-based quality assessment and inference in data-centric workflow executionspt_BR
dc.contributor.authorCaron, Clémentpt_BR
dc.contributor.authorAmann, Berndpt_BR
dc.contributor.authorConstantin, Cameliapt_BR
dc.contributor.authorGiroux, Patrickpt_BR
dc.contributor.authorSantanchè, Andrépt_BR
unicamp.authorSantanchè, A., Univ. de Campinas (UNICAMP)São Paulo, Brazilpt_BR, C., Airbus Defence and SpaceVal-de-Reuil, France, LIP6 - Univ. de Pierre et Marie Curie (UPMC)Paris, Francept, B., LIP6 - Univ. de Pierre et Marie Curie (UPMC)Paris, Francept, C., LIP6 - Univ. de Pierre et Marie Curie (UPMC)Paris, Francept, P., Airbus Defence and SpaceVal-de-Reuil, Francept
dc.subjectSistemas de gestão de fluxo de trabalhopt_BR
dc.subjectFluxo de trabalho - Processamento de dadospt_BR
dc.subjectWeb semânticapt_BR
dc.subjectRecuperação da informaçãopt_BR
dc.subjectInferência (Lógica)pt_BR
dc.subjectOntologias (Recuperação da informação)pt_BR
dc.subject.otherlanguageWorkflow management systemspt_BR
dc.subject.otherlanguageWorkflow - Data processingpt_BR
dc.subject.otherlanguageSemantic webpt_BR
dc.subject.otherlanguageInformation retrievalpt_BR
dc.subject.otherlanguageOntologies (Information retrieval)pt_BR
dc.description.abstractIn this article we present a rule-based quality model for data centric workflows. The goal is to build a tool assisting workflow designers and users in annotating, exploring and improving the quality of data produced by complex media mining workflow executions. Our approach combines an existing fine-grained provenance generation approach [3] with a new quality assessment model for annotating XML fragments with data/application-specific quality values and inferring new values from existing annotations and provenance dependencies. We define the formal semantics using an appropriate fixpoint operator and illustrate how it can be implemented using standard Jena inference rules provided by current semantic web infrastructures.en
dc.description.abstractIn this article we present a rule-based quality model for data centric workflows. The goal is to build a tool assisting workflow designers and users in annotating, exploring and improving the quality of data produced by complex media mining workflow execupt_BR
dc.relation.ispartofLecture notes in computer sciencept_BR
dc.identifier.citationLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). Springer Verlag, v. 8841, n. , p. 130 - 147, 2014.pt_BR
dc.description.sponsorshipsem informaçãopt_BR
dc.description.sponsordocumentnumbersem informaçãopt_BR
dc.description.provenanceMade available in DSpace on 2015-06-25T18:03:13Z (GMT). No. of bitstreams: 1 2-s2.0-84909998879.pdf: 369853 bytes, checksum: 4dcb0ad2b3c9d8695ff55ac0466559f3 (MD5) Previous issue date: 2014 Bitstreams deleted on 2021-01-04T14:26:03Z: 2-s2.0-84909998879.pdf,. Added 1 bitstream(s) on 2021-01-04T14:27:02Z : No. of bitstreams: 2 2-s2.0-84909998879.pdf: 442259 bytes, checksum: 79d71ebf16fd20ba832cb48ae440d7db (MD5) 2-s2.0-84909998879.pdf.txt: 44438 bytes, checksum: 7bcdfff077661cb074eed0fe925c3b04 (MD5)en
dc.description.provenanceMade available in DSpace on 2015-11-26T15:05:41Z (GMT). No. of bitstreams: 2 2-s2.0-84909998879.pdf: 369853 bytes, checksum: 4dcb0ad2b3c9d8695ff55ac0466559f3 (MD5) 2-s2.0-84909998879.pdf.txt: 44438 bytes, checksum: 7bcdfff077661cb074eed0fe925c3b04 (MD5) Previous issue date: 2014en
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dc.contributor.departmentDepartamento de Sistemas de Informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordQuality dimensionpt_BR
dc.subject.keywordService callpt_BR
dc.subject.keywordData provenancept_BR
dc.subject.keywordResource nodept_BR
dc.subject.keywordProvenance informationpt_BR
dc.type.formArtigo de eventopt_BR
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